DISCUSSION PAPER SERIES - THE SHORT-RUN MACRO IMPLICATIONS OF SCHOOL AND CHILD- CARE CLOSURES
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DISCUSSION PAPER SERIES
DP14882
THE SHORT-RUN MACRO
IMPLICATIONS OF SCHOOL AND CHILD-
CARE CLOSURES
Nicola Fuchs-Schündeln, Moritz Kuhn and Michèle
Tertilt
LABOUR ECONOMICS
MACROECONOMICS AND GROWTH
MONETARY ECONOMICS AND FLUCTUATIONSISSN 0265-8003
THE SHORT-RUN MACRO IMPLICATIONS OF
SCHOOL AND CHILD-CARE CLOSURES
Nicola Fuchs-Schündeln, Moritz Kuhn and Michèle Tertilt
Discussion Paper DP14882
Published 12 June 2020
Submitted 10 June 2020
Centre for Economic Policy Research
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Copyright: Nicola Fuchs-Schündeln, Moritz Kuhn and Michèle TertiltTHE SHORT-RUN MACRO IMPLICATIONS OF
SCHOOL AND CHILD-CARE CLOSURES
Abstract
The COVID19 crisis has hit labor markets. School and child-care closures have put families with
children in challenging situations. We look at Germany and quantify the macroeconomic
importance of working parents. We document that 26 percent of the German workforce have
children aged 14 or younger and estimate that 11 percent of workers and 8 percent of all working
hours are affected if schools and daycare centers remain closed. In most European countries, the
share of affected working hours is even higher. Policies to restart the economy have to
accommodate the concerns of these families.
JEL Classification: E24, E32, J22
Keywords: COVID-19, Labor market, children, child-care, Parents, workforce
Nicola Fuchs-Schündeln - fuchs@wiwi.uni-frankfurt.de
Goethe University Frankfurt and CEPR
Moritz Kuhn - mokuhn@uni-bonn.de
University of Bonn and CEPR
Michèle Tertilt - tertilt@uni-mannheim.de
University of Mannheim and CEPR
Acknowledgements
We thank Paul Reimers for excellent research assistance. Financial support from the Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation) (through the CRC-TR-224, project A3, two Leibniz Awards, and Germany's Excellence Strategy
-EXC 2126/1- 390838866.) is gratefully ac- knowledge.
Powered by TCPDF (www.tcpdf.org)The Short-Run Macro Implications of School and
Child-Care Closures∗
Nicola Fuchs-Schündeln† Moritz Kuhn‡ Michèle Tertilt§
June 10, 2020
Abstract
The COVID19 crisis has hit labor markets. School and child-care closures have put
families with children in challenging situations. We look at Germany and quantify
the macroeconomic importance of working parents. We document that 26 percent
of the German workforce have children aged 14 or younger and estimate that 11
percent of workers and 8 percent of all working hours are affected if schools and
child-care centers remain closed. In most European countries, the share of affected
working hours is even higher. Policies to restart the economy have to accommodate
the concerns of these families.
Keywords: COVID-19, labor market, children, child-care, parents, workforce
∗
We thank Paul Reimers for excellent research assistance. Financial support from the Deutsche
Forschungsgemeinschaft (DFG, German Research Foundation) (through the CRC-TR-224, project A3,
two Leibniz Awards, and Germany’s Excellence Strategy –EXC 2126/1– 390838866.) is gratefully ac-
knowledge.
†
Goethe University Frankfurt, CEPR, IZA, email: fuchs@wiwi.uni-frankfurt.de
‡
University of Bonn, ECONtribute, CEPR, IZA, email: mokuhn@uni-bonn.de
§
University of Mannheim, CEPR, IZA, email: tertilt@uni-mannheim.de
11 Introduction
Economies around the world have been faced with massive job losses—numbers in many
countries are approaching those of the Great Depression in the 1930s. The unemployment
rate in the United States reached 14.7 percent in April and 13.3 percent in May. Real-time
surveys even put it as high as 24 percent during the week of May 10-16, and 21 percent
during the week of May 24-30 (Bick and Blandin, 2020). Unlike in normal business
cycles, where fluctuations in hours are driven largely by men (Doepke and Tertilt, 2016),
the COVID19 recession has hit the employment of women particularly hard— partly due
to affected sectors with high female employment shares (such as retail and tourism), but
also because schools and daycare closures forced some mothers to leave their jobs (Alon
et al., 2020a; Torrejón Pérez et al., 2020). Germany has been impressively sheltered so
far. The unemployment rate in May 2020 stands at only 6.1 percent, but employers
rely massively on short-time work.1 Among workers employed in January, 13 percent are
currently (May 24) either on short-time work or employed but not working and 28 percent
of the workforce are currently working fully or partly from home (Blom et al., 2020).
We explore the labor market consequences of slowly “reopening” the economy and in-
creasing demand for physical presence at the workplace, without at the same time fully
reopening schools and child-care centers. We use the most recent 2018 data from the
European Labor Force Survey (EU-LFS) to report in a first step what fraction of the
workforce live with children in the household, and then estimate what fraction of workers
have to provide childcare if schools and child-care centers do not reopen to the extent the
economy does. In a second step, we also estimate what fraction of total hours will be lost
in the labor market and find that the macroeconomic impact due to parents’ inability to
work is likely large. The paper’s focus is on the German labor market but we use the
harmonized European data from the EU-LFS, complemented by the EU-SILC, to also
compare Germany to its European neighbors. While the fraction of potential hours lost
due to child-care obligation in Germany is large, it is even larger in most other European
countries, particularly the Scandinavian ones.
The rest of the paper is structured as follows. Section 2 describes the data sources, sample
selection, and definitions. Section 3 presents results for the German labor market and
Section 4 compares Germany to its European neighbors. We provide some conclusions
and an outlook in Section 5.
1
Data taken from Section 1.4.5 of the latest German labor market report, May 2020,
https://statistik.arbeitsagentur.de/Statistikdaten/Detail/202005/arbeitsmarktberichte/
monatsbericht-monatsbericht/monatsbericht-d-0-202005-pdf.pdf.
22 Data and Methodology
We use data from the 2018 rounds of the European Labor Force Survey (EU-LFS) and
the Statistics on Income and Living Conditions (EU-SILC). Due to larger sample size,
we primarily rely on the EU-LFS. However, for Denmark, Finland, Luxembourg, Norway,
Serbia, Sweden, and Switzerland, the EU-LFS does not contain a household identifier, and
thus for these countries we use EU-SILC data instead. For the countries for which we could
potentially use both data sets, we compared our statistics of interest across both data sets
and found only small differences except for Bulgaria. Therefore, we exclude Bulgaria from
the analysis. All statistics are calculated using survey weights. For Germany, the 2018
EU-LFS contains 527,000 observations, 261,000 of them being employed adults.
Rather than relying on detailed micro data on child-care arrangements, we closely follow
the methodology in Dingel et al. (2020) and estimate what percent of the workforce is
affected by school and child-care closings based on pre-crisis data on employment, hours,
and children across households. By doing this, we assume that children aged 14 or younger
cannot be left unsupervised alone at home. While many behavioral responses ought to
be expected after a large shock, the presence of children in the household seems largely
impossible to adjust in the short-run. Further, most margins that working parents use
in normal times (such as hiring baby-sitters, sharing childcare needs with neighbors and
friends, or grandparental care) are currently either explicitly banned by state law or at
least highly discouraged. Thus, the most likely margin of adjustment to the closures is
that one adult per household will stop working.
In a first step, we calculate the share of employed adults, defined as being aged 20 or
older, who live with children aged 14 or younger in the household. These adults comprise
the parents, but also potential step-parents, partners of one parent, friends or relatives, or
older siblings, as long as they live in the same household. We find that 94 percent of these
adults are either the head of the household or the spouse and thus very likely parents or
step-parents.2 We consider as potential caregivers in a household all individuals aged 20
to 74 who are non-employed. If no such individual is present in the household, we assume
that one of the working adults in the household has to stay at home to take care of the
children. When we analyze the hours lost due to this employed individual staying home,
we assume that the employed individual with the least usual hours worked within the
household will stay home.
2
The other employed adults are composed of 5.2 percent older siblings, 0.2 percent grandparents, and
0.6 percent other adults.
33 Results
We start by exploring the share of employed workers who have children aged 14 or younger
in their households. Results are given in Figure 1 and the first column of Table 1. Figure
1 shows that children are very prevalent among the German workforce. We find that one
out of four employed workers (25.9 percent) has children at home. To put this number
into perspective, these are about 11.5 million people, which is larger than the sum of all
workers in the German manufacturing and construction sector in 2018.3
Figure 1: Share of parents and working hours affected with childcare obligations
Childcare obligations of the employed - Germany
30
% Employed
with children
aged 0-14
25
% Employed with
children & no
caregiver
20
15 % Employed with
childcare
obligations % Usual hours of
employed with
10
childcare obligations
5
0
Notes: Figure shows the share of employed parents with childcare obligations, the share of parents with
childcare obligations but no available caregiver in the households, the share of employed parents with
childcare obligations taking over childcare if child-care is not available, and the hours reduction due
to parents taking over childcare obligations in case child-care is not available. See text for details of
estimation of these shares.
Comparing the first two bars in Figure 1, or the first two rows in Table 1, we see that
4 percent of households with children also include a non-working adult (such as a non-
working mother, an older sibling, or grandparents). Assuming that these non-working
adults could take over childcare and home schooling obligations, we still find that one in
five employees (21.2 percent) is without childcare if school and child-care centers remain
closed or reopen only partially.
Next, we take into account that watching children requires only one parent, not both
3
In 2018, there are 44.9 million employed in the German labor market, 7.7 million are work-
ing in manufacturing and 2.5 million are working in construction. Data taken from the German
statistical office https://www.destatis.de/DE/Themen/Arbeit/Arbeitsmarkt/Erwerbstaetigkeit/
Tabellen/arbeitnehmer-wirtschaftsbereiche.html?nn=206552.
4simultaneously. To estimate the share of workers who will be unable to work due to
childcare obligations, we assume that in each household one adult will stay home. This
share of employed workers corresponds therefore roughly to half of the couple households
plus the share of single households. In total, we estimate that about 11 percent of workers
would have to stay at home (Figure 1 or second panel of Table 1) with 9 percent of these
workers living in couple households and 2 percent being single parents. To put this number
into perspective, we compare it to the unemployment rate of 6.1 percent in May 2020.
Even if all unemployed workers in Germany would find work immediately, this would just
fill about half the jobs potentially left vacant due to parents’ inability to work.
Next, note that couples can, and likely will, optimize when choosing who will stay at
home. We follow a simple rule of thumb for this optimization. Within each of household
with childcare obligations, we identify the household member with the lowest regular
hours of work and assume that this person will stay at home.4 This approach results in
a total hours reduction of 8.4 percent (Figure 1 or fourth panel of Table 1), of which 6.8
percent stem from workers in couple households and 1.6 percent from single parents.
In the second to fourth columns, Table 1 also includes numbers separately for children
above and below the school entry age of 6. These numbers allow the assessment of hours
lost separating school from daycare closures. For example, if schools reopen but daycare
centers stay closed, still 9.8 percent of workers are affected: 6.3 percent of the employed
have only children under the age of 6 in the household and another 3.5 percent of the
employed have children of both ages. If we consider instead the consequences of daycare
centers reopening but schools staying closed, we find that 15 percent of workers would be
affected. These workers are composed of 11.5 percent households where all children are 6
years and older and another 3.5 percent where at least one child is of schooling age but
younger siblings are present. The age distinction might be important for another reason:
young children typically need more adult attention, while older children may be able to
play by themselves at least for some of the time. Thus, at least for those parents working
from home, the age of the children will also affect the opportunity to continue at least
some work while taking care of children.
We also look at the gender composition of the workers who will likely stay at home in case
of child-care and school closures. Within couple households, we find that in 82 percent
of households, mothers work fewer hours than fathers (third panel of Table 1). In 10
percent of families, both spouses work equal hours, while only in 8 percent of the cases,
4
Of course in reality the choice who will stay at home also depends on social norms and relative wages
in the family. A full analysis of such choices is beyond the scope of this paper. Alon et al. (2020b) provide
a detailed model of the household division of work and childcare in the face of COVID19 and apply it to
the United States.
5Table 1: Share of parents and working hours affected with childcare obligations
Children All chil- All chil- Children
0-14 dren un- dren age of both
der 6 6-14 ages
Share of employed individuals
with children 0.259 0.081 0.133 0.045
with children & no available caregiver in house- 0.212 0.063 0.115 0.035
hold
Share of employed taking over childcare obligations
all 0.112 0.033 0.061 0.018
households with 2+ members 0.093 0.029 0.048 0.016
single parents 0.018 0.004 0.013 0.002
Gender composition of parents with lower hours in all employed with childcare obligations
Share of women 0.816 0.766 0.830 0.860
Share of men 0.083 0.095 0.084 0.058
Equal hours of women and men 0.101 0.139 0.086 0.083
Share of usual hours by employed individual w/ childcare obligations
all 0.084 0.026 0.046 0.012
in households with 2+ members 0.068 0.023 0.034 0.011
single parents 0.016 0.003 0.012 0.001
Notes: Table shows share of employed parents with childcare obligations and their working hours. First
part of the table (share of employed) shows the share of all parents. The lower part of the table shows
the share in total hours worked. First column show the shares for workers (hours) with all children 14
years and younger. Columns 2 to 4 split in groups where all children are 6 years and younger, where all
children are 6 to 14 years, and for workers in households with children in both age groups. The sum over
columns 2 to 4 corresponds to column 1.
the father is working fewer hours. Thus the majority of hours lost to the labor market
will likely be in female dominated occupations (such as education, health care, law and
administration and sales).5 Surprisingly, the share of females in employed individuals
with childcare obligations is lowest in the group where all children in the household are
6 years and younger. While we do not explore the reasons for this pattern, institutional
features of the maternity and paternity leave programs could play a role as they also
encourage fathers to go on paternity leave. We find the highest share of females in the
group where children are in both age groups, below 6 years and 6 to 14 years. In this
groups, 86 percent of mothers work fewer hours than fathers, and only in 8 percent of
5
In each of these occupations the share of women is above 70 percent in Germany. See employ-
ment statistics for workers covered by social security legislation of the German employment office, lat-
est data September 2019, https://statistik.arbeitsagentur.de/Statistikdaten/Detail/201909/
iiia6/beschaeftigung-sozbe-bo-heft/bo-heft-d-0-201909-xlsx.xlsx.
6households fathers and mothers work equally many hours.
To gauge the immediate macroeconomic effect of the school and child-care closures, we
compare the estimate of 8.4 percent lost hours due to employed individuals having to take
over childcare duties to a popular policy instrument to deal with labor underutilization,
namely short-time work. Short-time work programs were very prevalent during the finan-
cial crisis and are also heavily used now.6 In 2009, more than 1.1 million workers were on
short-time work with an hours reduction of about one third of their working time (28.1
percent).7 In other words, during the financial crisis 3.1 percent of all employed workers
were on short-time work and their hours reduction accounted for 1 percent of total hours
worked in 2009. While these were massive programs, the numbers get dwarfed by the
impact of the likely hours reduction of parents during the current crisis. Based on the
numbers in Table 1, we estimate that close to four times as many workers and more than
eight times the share of hours would be lost due to parents’ inability to work due to
childcare obligations. Even if we overestimate the share of affected hours, because some
children can stay alone for some time, some parents can work from home while simulta-
neously taking care of their children, or some other child-care arrangements like sharing
between families or involving grandparents are used, it is clear that the impact of the
child-care and school closings on hours worked is large. Most of the reduction of hours
will likely come from women.
4 European Evidence on Parents in the Labor Mar-
ket
In this section, we broaden our perspective and look at how the labor market situation in
Germany compares to other European countries. Figure 2 compares the share of employed
individuals with children across the European countries. We portray the countries in four
regions (Scandinavia, Western Europe, Eastern Europe, and Southern Europe), ordered
alphabetically within a region. Region averages are marked with horizontal lines. The
first striking observation is that the share of employed workers who have children in the
household is lowest in Germany compared to all other European countries. We find the
6
Current cumulative applications for short-time work stand at 10.7 million and constitute an upper
bound for the number of short-time workers in May. Data taken from Section 1.2.3 of the latest German
labor market report, May 2020, https://statistik.arbeitsagentur.de/Statistikdaten/Detail/
202005/arbeitsmarktberichte/monatsbericht-monatsbericht/monatsbericht-d-0-202005-pdf.
pdf.
7
Data on short-time workers and hours reduction are taken from the working time statistics of the
Institute for Employment research (IAB) http://doku.iab.de/arbeitsmarktdaten/AZ_Komponenten.
xlsx.
7largest shares in Ireland and Poland with over 40 percent compared to 26 percent in
Germany (Table A.1 in the appendix contains the country-specific numbers shown in
Figures 2 to 5). There are several reasons for the low share in Germany: first, and most
importantly, Germany has a low fertility rate. Secondly, compared to the other European
countries, a relatively large share of children in Germany live in households in which no
adult is employed. Third, a relatively low share of households with at least one employed
adult has exactly one child. Overall, the share of employed individuals with children is
relatively similar across the European regions, but with substantial variation within a
region.
When it comes to the share of employed individuals with no available caregiver in Figure
3, we find the lowest average shares in Eastern and Southern Europe. In these regions,
the employment rates of married women are relatively low (Bick and Fuchs-Schündeln,
2018; Bick et al., 2019), and thus in many households mothers do not work and can take
care of the children. The share of employed individuals with no available caregiver is
therefore lower in Hungary, Serbia, and the Slovak Republic than in Germany. Figure
4 then calculates the share of employed individuals with childcare obligations, largely
preserving the ordering across countries.8
Last, analyzing the share of usual hours by employed individuals with childcare obliga-
tions, we find that only Serbia with 7.7 percent has a lower share than Germany with
8.4 percent. We find the largest shares in terms of affected hours in the Scandinavian
countries Sweden (15.7 percent) and Denmark (15.5 percent), and in France (15.7 per-
cent); Appendix Figure A.1 shows the same information in descending order.9 Comparing
the share of employed with childcare obligations in Appendix Table A.1 to the share of
usual hours in the same table provides an estimate of how prevalent part-time is among
employed adults with children. We find that the ratio of hours to employed is lowest in
Austria with 0.72 but then immediately followed by Germany with 0.75. We find the
highest share in Latvia with over 0.97 but find again that especially in the Scandinavian
countries but also in France the share is high with typically 0.9 or above. Summarizing,
the share of hours lost due to child-care and school closures in Germany is with 8.4 per-
cent substantial, but small in European comparison. It is almost twice as high in Sweden,
Denmark, and France.
8
One would expect a difference here if the household composition, i.e., the distribution of single versus
couple households or households with more than two adults, would be very different across countries.
9
We conjecture that these numbers might have been one of the reasons why Denmark was among the
first countries to reopen schools in mid April, and Sweden never closed them.
8Figure 2: Share of employed individuals with children
50
45
40
35
30
Share (%)
25
20
15
10
5
0
K
N N
SWR
E
BET
C L
D E
FRU
G A
BR
LU L
N X
LD
ESE
H T
H V
LTN
LVU
POA
R L
SRM
SVB
SV K
N
ESP
G P
C
PRA
T
IR
AU
N
H
Z
R
Y
IT
FI
O
E
U
R
O
C
C
D
Western Eastern Southern
Scandinavia
Europe Europe Europe
Notes: Share of all employed individuals who have children aged 14 or younger in their household across
European countries. Germany shown in orange. Horizontal red lines show region averages. Results based
on EU-LFS data except for Switzerland, Denmark, Finland, Luxembourg, Norway, Serbia, and Sweden
where EU-SILC data is used. See text for further details.
9Figure 3: Share of employed individuals with children but no available caregiver
50
45
40
35
30
Share (%)
25
20
15
10
5
0
K
N N
SWR
E
BET
C L
D E
FRU
G A
BR
LU L
N X
LD
ESE
H T
H V
LTN
LVU
POA
R L
SRM
SVB
SV K
N
ESP
G P
C
PRA
T
IR
AU
N
H
Z
R
Y
IT
FI
O
E
U
R
O
C
C
D
Western Eastern Southern
Scandinavia
Europe Europe Europe
Notes: Share of all employed individuals who have children aged 14 or younger in their household but no
available caregiver across European countries. Potential caregivers are all non-working adult household
members age 20 to 74. Germany shown in orange. Horizontal red lines show region averages. Results
based on EU-LFS data except for Switzerland, Denmark, Finland, Luxembourg, Norway, Serbia, and
Sweden where EU-SILC data is used. See text for further details.
10Figure 4: Share of employed individuals with childcare obligations
20
15
Share (%)
10
5
0
K
N N
SWR
E
BET
C L
D E
FRU
G A
BR
LU L
N X
LD
ESE
H T
H V
LTN
LVU
POA
R L
SRM
SVB
SV K
N
ESP
G P
C
PRA
T
IR
AU
N
H
Z
R
Y
IT
FI
O
E
U
R
O
C
C
D
Western Eastern Southern
Scandinavia
Europe Europe Europe
Notes: Share of all employed individuals taking over childcare obligations in case of child-care and school
closures for children aged 14 or younger in their household across European countries. Germany shown in
orange. Horizontal red lines show region averages. Results based on EU-LFS data except for Switzerland,
Denmark, Finland, Luxembourg, Norway, Serbia, and Sweden where EU-SILC data is used. See text for
further details.
11Figure 5: Share of usual hours by employed individuals with childcare obligations
20
15
Share (%)
10
5
0
K
N N
SWR
E
BET
C L
D E
FRU
G A
BR
LU L
N X
LD
ESE
H T
H V
LTN
LVU
POA
R L
SRM
SVB
SV K
N
ESP
G P
C
PRA
T
IR
AU
N
H
Z
R
Y
IT
FI
O
E
U
R
O
C
C
D
Western Eastern Southern
Scandinavia
Europe Europe Europe
Notes: Share of all usual hours worked by individuals taking over childcare obligations in case of child-
care and school closures for children aged 14 or younger in the household across European countries.
Usual hours of household member with the least usual hours taken for calculation. Germany shown in
orange. Horizontal red lines show region averages. Results based on EU-LFS data except for Switzerland,
Denmark, Finland, Luxembourg, Norway, Serbia, and Sweden where EU-SILC data is used. See text for
further details.
125 Conclusion and Outlook
From a macroeconomic perspective, the labor supply of parents who would have to stay
home if economic activity fully resumes and schools and child-care facilities remain closed
is massive. We estimate the share of affected employed workers to be close to twice the
number of all unemployed workers in Germany, and their share in hours worked is eight
times the work reduction due to short-time work during the financial crisis. While we
acknowledge that workers might find creative solutions and organize childcare in a way
to best deal with this situation, the macroeconomic labor supply effects are still so large
that policy seems well advised to take parents’ labor market situation into account when
developing plans for restarting the economy.
While this paper focuses on current labor supply of parents, it is important to emphasize
the potential long-run distributional and growth consequences that closed schools and
child-care centers have for society. First, if mothers reduce their hours by more than
fathers, this will lead to a widening of the gender wage gap. We have documented that
in 82 percent of couples, the mother is working fewer hours and will likely step in for
additional childcare needs (see also Jessen and Waights, 2020). First numbers from real-
time surveys in Germany provide evidence that mothers do indeed take over more childcare
needs than fathers (Adams-Prassl et al., 2020; Möhring et al., 2020; Kohlrausch and Zucco,
2020).10 Already in normal times, career interruptions of women lead to a widening of the
gender pay gap by age. Bayer and Kuhn (2019) demonstrate that starting at age 30, when
children are young and need childcare, the gender-career gap opens up and contributes 50
percent to the gender-pay gap 20 years later. The reasons are the missing steps climbed
on the career ladder by women which are likely due to women’s time out of the labor
force when children are young. Similarly, Kleven et al. (2019) estimate a child penalty of
about 60 percent of earnings still ten years after the birth of the first child in Germany.
These gaps will further widen if women take over the majority of childcare needs caused
by closed schools and daycare centers.
A second channel relates to the children themselves who clearly learn less if schools are
closed. Receiving less formal education will affect especially those children at the bot-
tom of the income distribution and thereby further decrease intergenerational mobility.
Wössmann (2020) provides an excellent survey of the literature that estimates the eco-
nomic costs of missed learning opportunities and its contribution to income inequality
(see also Furceri et al. (2020); Burgess and Sievertsen (2020)).
In sum, beyond the immediate impact on the current workforce, school and child-care
10
Similarly, von Gaudecker et al. (2020) provide evidence for the Netherlands.
13closures today will thus likely negatively affect intergenerational mobility and gender
equality in the workplace.
A Appendix
Figure A.1: Share of usual hours by employed individuals with childcare obligations: descending order
20
15
Share (%)
10
5
0
E
D A
SV K
N
PRT
T
A
L
N
N U
R
LU L
C X
YP
ZE
ES L
G P
R R
M
V
G D
H C
N
C A
E
SV T
D K
EU
B
BE
IR
PO
ES
AU
SW
FR
N
LV
R
IT
H
SR
FI
LT
O
B
L
R
U
O
C
N
H
Western Eastern Southern
Scandinavia
Europe Europe Europe
Notes: Share of all usual hours worked by individuals taking over childcare obligations in case of child-
care and school closures for children aged 14 or younger in the household across European countries.
Usual hours of household member with the least usual hours taken for calculation. Results based on EU-
LFS data except for Switzerland, Denmark, Finland, Luxembourg, Norway, Serbia, and Sweden where
EU-SILC data is used. See text for further details.
14Table A.1: Share of employed individuals and hours worked affected by childcare obligations
% employed with % usual hours by emp.
Country with children with chil- with childcare with childcare
dren and no obligations obligations
caregiver
AUT 30.9 24.9 12.5 9.0
BEL 37.3 31.0 16.3 13.7
CHE 29.6 24.3 14.3 9.6
CYP 36.3 27.3 14.0 12.5
CZE 34.4 25.4 13.5 12.5
DEU 25.9 21.2 11.2 8.4
DNK 35.8 31.7 17.2 15.5
ESP 36.4 26.2 13.5 11.7
EST 34.8 27.6 16.0 14.7
FIN 33.8 27.7 14.6 13.4
FRA 38.8 31.8 17.4 15.7
GBR 35.4 29.0 15.3 11.7
GRC 33.7 22.5 11.5 10.0
HRV 37.9 23.9 11.7 11.1
HUN 31.0 20.1 10.4 9.7
IRL 41.0 31.9 16.2 13.1
ITA 33.3 22.3 11.6 9.6
LTU 31.6 25.8 14.2 13.2
LUX 37.6 28.7 15.2 12.9
LVA 36.7 27.5 14.1 13.8
NLD 31.8 27.8 13.1 10.3
NOR 33.1 30.5 16.3 13.1
POL 41.3 25.6 12.8 11.9
PRT 35.8 28.6 14.8 14.0
ROM 39.9 25.8 12.0 11.5
SRB 39.9 18.7 9.3 7.7
SVK 34.3 19.7 9.6 8.7
SVN 37.3 31.6 15.7 14.8
SWE 35.9 32.1 17.5 15.7
Notes: Share of all employed individuals who have children aged 14 or younger in their household, who
have children and no available caregiver, who take over childcare obligations in case of school and child-
care closures, and share of all usual hours worked by individuals with childcare obligations in case of
child-care and school closures across European countries. Potential caregivers are all non-working adult
household members age 20 to 74. Usual hours of household member with the least usual hours taken
for calculation. Germany shown in orange. Horizontal red lines show region averages. Results based
on EU-LFS data except for Switzerland, Denmark, Finland, Luxembourg, Norway, Serbia, and Sweden
where EU-SILC data is used. See text for further details.
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